Alzheimer's disease (AD) is rapidly reaching epidemic proportions in the United States, currently affecting more than 5 million individuals and predicted to affect 14 million by 2050. Despite a general consensus that the amyloid-beta (Abeta) protein plays a significant role in disease progression, the underlying pathology of the disease is not entirely clear. Caenorhabditis elegans is a simple organism that has been used as a model for basic mechanistic studies on the underlying pathological processes involved in AD. Previous studies from our labs demonstrated that transgenic C. elegans with muscle specific expression of human Abeta undergo rapid paralysis, and worms with neuronal expression of Abeta show deficits in chemotaxis to volatile chemicals. In this study, we evaluate the effect of neuron specific expression of Abeta on multiple neuronally controlled behaviors in a transgenic C. elegans. These worms demonstrate deficits in odorant preference associative learning behavior, and the serotonin-controlled behaviors experience-dependent learning and egg laying. These newly identified learning-deficit behavioral phenotypes in the neuronal Abeta C. elegans suggest that the model may be used to elucidate underlying pathological events related to development of AD and for pharmaceutical intervention.

Cervical cancer is the second most common malignancy among women worldwide, with over 490000 cases diagnosed and 274000 deaths each year. Although current screening methods have dramatically reduced cervical cancer incidence and mortality in developed countries, a “See and Treat” method would be preferred, especially in developing countries. Results from our previous work have suggested that Raman spectroscopy can be used to detect cervical precancers; however, with a classification accuracy of 88%, it was not clinically applicable. In this paper, we describe how incorporating a woman's hormonal status, particularly the point in menstrual cycle and menopausal state, into our previously developed classification algorithm improves the accuracy of our method to 94%. The results of this paper bring Raman spectroscopy one step closer to being utilized in a clinical setting to diagnose cervical dysplasia. Posterior probabilities of class membership, as determined by MRDF-SMLR, for patients regardless of menopausal status, and for pre-menopausal patients only

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PFDs are prevalent in gynecologic cancer survivors and this is an important area of clinical concern and future research.